DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status
This action is in response to the amendment filed on 7/8/2026. Claims 1, 3-10, 12-19, 21, are pending. Claims 1, 7, 8, 10, 16, 17, and 19 are amended. Claim 21 has been added. Claims 2, 11, 20 had been previously cancelled.
Response to Arguments
Applicant's arguments filed 7/8/2026 have been fully considered but they are not persuasive. The applicant has argued the previous 101. Specifically “Applicant submits that no reasonable interpretation of amended independent claims 1, 10, and 19 would characterize these claims, especially when considered as an ordered combination of the recited steps/elements, as generic computer functions recited at a high level of generality.” The examiner respectfully disagrees. The problem that the applicant has identified, the sheer volume of regulatory filings making manual review impractical, and the resulting inability to find intelligence at scale is not a problem in computer technology. This is the abstract idea itself. Retrieving a large volume of data from a database, extracting information from it, and analyzing it to produce a useful output is an abstract idea. The fact that EDGAR contains hundreds of thousands of fillings and that a human could not read all of them does not distinguish this case from that of Electric Power Group where the data source was similarly voluminous and specific. Identifying an identifier combining historical records, and determining a future value form historical data are themselves generic data processing functions that are insufficient to integrate a judicial exception into a practical application. Merely reciting a greater number of generic data processing steps does not amount to a technical improvement. Further, the claims do not recite how the real-time modification is technically achieved; the applicant merely states the result. The modification happens in real time based on user behavior which is merely using a computer as a tool to perform an abstract idea faster. An improvement to the accuracy or efficiency of the financial forecast that the AI model produces is an improvement to the abstract idea (i.e. the quality of the financial prediction) not to the functioning of the computer or the AI model as a technology. The claims describe training an AI model on data so that its predictions are more accurate, which is an improvement in the informational/financial results, not in the computer functionality. Specifically, as claimed it appears that the invention is merely using as a computer as a tool to access information. Although the claims include the term large language model the claim itself does not include the language of a large amount of data, merely the training of an algorithm with the LLM “to analyze trading and transaction patterns.” In Electric Power Group v. Alstom the Federal Circuit held that claims directed to collecting data from multiple sources including specific, real world power grid data analyzing it, and displaying the results were abstract, even though the data source was specific and the scale was large. The court held that merely selecting a particular source of data does not transform an abstract data analysis method into a practical application. Data gathering is not a technical improvement. Even highly specific financial data sources and computation do not constitute practical application when the improvement is to the financial analysis itself rather than the underlying computer technology. Retrieving data from a publicly accessible internet database (even Edgar) is performing a generic computer function. The claims use Edgar as an input not as a technical component that the invention improves or transforms. Edgar is merely being used as a data source. Edgar arguably at most improves the abstract idea it does not improve how the data is retrieved, how the technology functions, or how the models are trained. Applicant’s arguments are not found persuasive.
The applicant has argued “Moreover, the claimed features significantly improve the computer functionality by leveraging and integrating various APIs, workflow automation tools, LLM tools, and AI tools onto a single system or platform. For example, independent claims 1, 10, and 19 recite internally modified APIs, as well as an internally trained LLM component that are leveraged to generate the output/forecast. Particularly, this combination increases speed, efficiency, consistency, and accuracy of computing associated with the forecasting of future executions, as compared to conventional systems that rely on third-party systems and unintegrated software. Thus, these claimed elements significantly improve computing functionality over conventional systems and technology.” The examiner respectfully disagrees. Combining several known generically functioning software components onto a single platform, which each components still performing its own conventional, expected function, in this case is not a technical improvement. Internally modified APIs and internally trained LLM used to generate the output describes performing the same abstract process using integrated, in house tools rather than external ones is merely a difference in where and by whom the generic functions are hosted, not a difference in the underlying computing technology. Avoiding reliance on third-party systems and manual integration of separate software tools is at most an organizational or business efficiency. Reducing coordination overhead an inconsistency that may arise from using multiple external venders is not a technical improvement to how the computer itself processes data.
The applicant has argued “Furthermore, Applicant respectfully submits that the above-described improvements made by the recited features integrate the claims into a practical application and the § 101 rejection should be withdrawn for reasons similar to those set forth by the Appeals Review Panel (ARP) in its decision on request for rehearing in Ex parte Desjardins et al. In that decision the panel held that "claims directed to an improvement in the functioning of a computer, an improvement to other technology or technical field are patent eligible." In that case, the panel held that because the claimed system used less storage capacity and enabled a reduction in system complexity, the claims reflected sufficient improvement so as to be integrated into a practical application. See the ARP's decision on request for rehearing in Ex parte Desjardins et al. (Appeal No. 2024-000567, dated September 26, 2025) at pages 8 and 9. Similarly, the claimed features recite generating a plurality of specific APIs that are integrated to generate various insight information that are used to particularly train and improve the performance of an AI model.” The examiner respectfully disagrees. In Desjardins the technical improvement was to the computer system itself. The improvements were to how the computer operates. Applicant’s claims are directed to accuracy and efficiency of financial predictions, which would at most be an improvement to the quality of the output in the financial data, not to how the technology itself operates. The system at most produces better financial forecasts. The improvement in Desjardins was to the technology the improvement here appears to be in the financial analysis (abstract idea). Further, applicant’s claimed feedback loop in the claims appears to improve a system ability to predict financial trades. In Desjardins the improvement was to a technical operation. The claims do not explicitly recite what technical result the feedback loop and the API modification produce in the functioning of the computer. Applicant’s originally filed specification supports that the focus of the invention is to improving commercial sales rather than a technical improvement.
The applicant has argued “Additionally, these claims have been amended to recite a particular ordered combination of claimed elements, such that the claimed combination of elements contain an inventive concept. Applicant respectfully submits that each element must be examined as "as an ordered combination" of elements. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 218 n.3 (2014). Particularly, the Federal Circuit has held that "an inventive concept can be found in the non- conventional and non-generic arrangement of known, conventional pieces." See Bascom Global Internet Services v. AT&T Mobility, 827 F. 3d 1341 (2016). Applicant respectfully submits that the ordered combination of claimed elements defines a non-conventional arrangement, such that the ordered combination set forth in the claims is not routine or conventional. This conclusion is supported by the fact that no prior art is applied to reject these claimed features. Moreover, the Examiner has not established that the combination of claim features is well-understood, routine, or conventional, as required by MPEP 2106.05(d)(I).” The examiner respectfully disagrees. Applicant has not identified an analogous unconventional technical arrangement here. The claimed sequence retrieve data, build a knowledge graph from it, generate and modify APIs to analyze it, train an AI model on it, and forecast an output follows the ordinary, expected sequence in which a person would perform such a data-processing and machine-learning task. For example collect the data, build a representation of it, build and tune analytical tools, then apply those tools to produce a result. An ordered combination of generic components performing their generic functions in their ordinary sequence does not become "non-conventional" simply because the resulting process, as a whole, is new. The question under Step 2B is whether the combination reflects a non-conventional technical arrangement, not merely a novel one. As to applicant's argument that the lack of an applied prior art rejection establishes that the combination is not well-understood, routine, or conventional, novelty and eligibility are separate inquiries, and the absence of prior art is not evidence of eligibility. "The novelty of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter." Berkheimer does not require a factual finding that every claim element is well-understood, routine, and conventional. The Berkheimer inquiry applies specifically to the additional elements beyond the abstract idea here, the generic processor, communication interface, API framework, and LLM technology used in their ordinary capacity to receive, store, transmit, and process data. It is well-understood, routine, and conventional to use a processor, APIs, and a machine-learning model to receive input data, perform computational analysis, and output a result. The applicant has not identified any additional element, or combination of additional elements, that is itself unconventional. The alleged inventiveness lies in the abstract idea (the financial forecasting methodology) rather than in the generic computer components used to implement it. The independent claims do not to improve the functioning of the processor or mediums. As is stated above, claim 1 does not affect an improvement in any other technology or technical field. Thus, claim 1 at issue amounts to nothing significantly more than instructions to apply the abstract idea of information access using some unspecified, generic computer. The previous 101 rejection is maintained and updated in view of applicant’s amendments. Accordingly, the claims do not recite significantly more than the identified judicial exception, and the rejection under 35 U.S.C. 101 is maintained.
The applicant has argued “But this conclusion does not apply to amended claims 1, 10, and 19. These claims do not recite commercial interactions. Rather, the claims recite computer-based applications for actively generating and modifying various APIs to generate insight information used to train an AI model for forecasting future transaction executions. Particularly, the claims are directed to a particularly recited system that includes a plurality of generated APIs in combination with a trained AI model for predicting future transactions that are likely to occur. Moreover, the recited plurality of APIs are performing a multitude of active steps that include identifying market identifiers and common identifiers, amalgamating transaction histories, and determining future behaviors. The claims are not directed to merely collecting, analyzing, and reporting results. Thus, the above argument does not apply to amended claims 1, 10, and 19.” The examiner respectfully disagrees. According to applicant’s originally filed disclosure the background of the invention is to help a salesperson at a financial institution predict what a client will want to buy next, so they can pitch it to them. This is at its core a commercial interaction because it is about facilitating a sale between two parties (see originally filed specification ¶ 3). The claims recite retrieving information related to a government filing, generating a knowledge graph, generating an API, generating insight information, retrieving information, analyzing the information to generate a workflow, modifying an API based on a workflow, training an algorithm to analyze trading and transaction patterns, storing the information, leveraging to generate a feedback loop, and forecasting a proposed future transaction. Claim 1 involves gathering data about a client, analyzing their past behavior, predicting their future behavior, and using that prediction to facilitate a commercial truncation which is clearly directed to forecasting market/purchase activity (gather, analyze, predict). The Federal Circuit has held similar concepts to be abstract. For example, the Federal Circuit has held that abstract ideas include the concepts of collecting data, analyzing the data, and reporting the results of the collection and analysis, including when limited to particular content. See, e.g., Intellectual Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1340–41 (Fed. Cir. 2017) (identifying the abstract idea of organizing, displaying, and manipulating data); Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016) (characterizing collecting information, analyzing information by steps people go through in their minds, or by mathematical algorithms, and presenting the results of collecting and analyzing information, without more, as matters within the realm of abstract ideas). Thus, under the first prong, claim 1 recites the patent-ineligible judicial exception of certain methods of organizing human activity commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The receiving data, manipulating data, and forecasting data are all directly related to financial instruments.
The applicant has argued “Additionally, amended claims 1, 10, and 19 do not recite a mental process. Rather, amended claims 1, 10, and 19 recite a particularly recited system that includes a plurality of generated APIs in combination with a trained AI model such that the various APIs actively generate insight information used to train an AI model for forecasting future transaction executions. Particularly, the claims recite retrieving and analyzing all derivatives in an EDGAR database, which cannot be practically performed in the human mind. Additionally, the recited plurality of APIs are performing a multitude of active steps that include identifying market identifiers and common identifiers, amalgamating transaction histories, and determining future behaviors, which are not mental steps. Moreover, the API are modified in real-time by real-time user behavior, which cannot be done mentally. Thus, this computer-dependent process is incapable of being practically performed in the human mind as required by MPEP 2106.04(a)(2)III(A). Thus, amended independent claims 1, 10, and 19 cannot be classified as an abstract idea.” The examiner respectfully disagrees. Claims can recite a mental process even if they are claimed as being performed on a computer. The focus of the claim, in view of the specification, is predicting future trades to facilitated sales which is a judgement that a human skilled in the art could do mentally. The use of technology in the steps of the claims is merely just a mechanism for doing the steps faster. The predicted future transaction is a prediction that an experience analyst makes mentally every day. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures “can be carried out in existing computers long in use, no new machinery being necessary.” 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of “anonymous loan shopping” recited in a computer system claim is an abstract idea because it could be “performed by humans without a computer”). The applicant is claiming technology but it is at a very high level. The applicant is merely using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower’s credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of “anonymous loan shopping”, which was a concept that could be “performed by humans without a computer.” 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes.
The applicant has amended the claims to overcome the previous 103 rejections. The closes prior art includes Zhu et al. (US 20220269936 A1) discloses structuring a machine learning model to forecast a prediction using the time series data, the machine learning model structured to integrate the knowledge graph structure as an error term in the machine learning model. Coyle et al. (US 20240265456 A1) discloses predicting unknown values for assets based on reported data posted on a central repository. Roy et al. (US 20210385124 A1) discloses the creation and use of APIs. Shatsky et al. (US 20240296350 A1) discloses updating and manipulating knowledge graphs. Leyden et al. (US 20200218406 A1) discloses multiple features of APIs. Although APIs, AI algorithms, and LLMs existed in the prior art the limitations of the specifics of storing the modified at least one API, the first information, and the generated workflow in the LLM, and leveraging, via the LLM, the modified at least one API to generate a positive feedback loop for enabling future trading behavior prediction, wherein the forecasting comprises applying the trained AI algorithm to the first knowledge graph to generate the at least one proposed future transaction as well as the government filing, wherein the first information includes all derivatives in an electronic data gathering, analysis, and retrieval (EDGAR) database over a predetermined period of time are not found in the prior art does not anticipate or render obvious the claimed invention. It is because of the combination of elements that the previous 103 rejection was withdrawn.
The applicant has amended the claims to overcome the previous 112(b), second paragraph rejections. The previous 112(b), second paragraph rejections are withdrawn.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-10, 12-19, 21 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without anything significantly more.
Step 1: Claims 1, 3-9, 21, are directed to a method, claims 10, 11-18, are directed to an apparatus, and claim 19 is directed to a non-transitory computer readable medium. Therefore, claims 1, 3-10, 12-19, 21 are directed to patent eligible categories of invention.
Step 2A, Prong 1: Claims 1, 10, 19, recite a method for forecasting a future transaction, constituting an abstract idea based on “Certain Methods of Organizing Human Activity” related to commercial or legal interactions (including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations). Claim 1 recites abstract limitations including “A method for forecasting market activity, the method comprising: retrieving, …first information that relates to at least one form that corresponds to a government filing, wherein the first information includes all derivatives… over a predetermined period of time; generating, … based on the first information, a first knowledge graph that relates to a first entity; generating, … is customized for the entity and analyzes the first information and the first knowledge graph; wherein the at least one … is generated by leveraging a corpus of derivative data associated with the first information, and wherein the at least one … includes: a first … that identifies a market identifier associated with the first entity, a second …that identifies a common identifier related to a second entity that executes transactions with respect to the first entity, a third … that amalgamates a transaction history associated with the first entity, and a fourth … that determines a future behavior of the second entity in relation the market identifier; generating, …, insight information into at least one financial instrument that relates to the first entity; retrieving, …, second information that relates to historical actions performed by at least one person that is associated with the first entity and that is based on the generated insight information; analyzing, …, the first information and the second information to automatically generate a workflow; automatically modifying, …, based on the generated workflow and real-time user behavior; training, … by using the retrieved second information to analyze trading and transactional patterns, wherein the training …includes: storing the modified …, the first information, and the generated workflow …, and leveraging, …, the modified … to generate a positive feedback loop for enabling future trading behavior prediction; and forecasting, … at least one proposed future transaction to be executed with respect to the at least one financial instrument that relates to the first entity, wherein the forecasting comprises: forecasting a thematic concept with respect to a set of financial instruments based on outputted results…, using the trained … model to analyze trading and transactional patters associated with the first knowledge graph.” Claim 10 recites abstract limitations including “…retrieve … first information that relates to at least one form that corresponds to a government filing; generate, based on the first information, a first knowledge graph that relates to a first entity…is customized for the entity and analyzes the first information and the first knowledge graph; a first … that identifies a market identifier associated with the first entity, a second …that identifies a common identifier related to a second entity that executes transactions with respect to the first entity, a third … that amalgamates a transaction history associated with the first entity, and a fourth … that determines a future behavior of the second entity in relation the market identifier; generate… insight information into at least one financial instrument that relates to the first entity; retrieve second information that relates to historical actions performed by at least one person that is associated with the first entity and that is based on the generated insight information; analyze the first information and the second information to automatically generate a workflow; automatically modify … based on the generated workflow; train … model … by using the retrieved second information to analyze trading and transactional patterns, wherein the training of the …model includes: storing the modified…, the first information, and the generated workflow .., and leveraging, …, the modified … to generate a positive feedback loop for enabling future trading behavior prediction; and forecast,…, at least one proposed future transaction to be executed with respect to the at least one financial instrument that relates to the first entity, wherein the forecasting comprises: forecasting a thematic concept with respect to a set of financial instruments based on outputted results… using the trained … model to analyze trading and transaction patterns associated with the first knowledge graph. Claim 19 recites abstract limitations including “ retrieve… first information that relates to at least one form that corresponds to a government filing; generate, based on the first information, a first knowledge graph that relates to a first entity; … is customized for the entity and analyzes the first information and the first knowledge graph; a first … that identifies a market identifier associated with the first entity, a second …that identifies a common identifier related to a second entity that executes transactions with respect to the first entity, a third … that amalgamates a transaction history associated with the first entity, and a fourth … that determines a future behavior of the second entity in relation the market identifier; generate… insight information into at least one financial instrument that relates to the first entity; retrieve second information that relates to historical actions performed by at least one person that is associated with the first entity and that is based on the generated insight information; analyze the first information and the second information to automatically generate a workflow; automatically modify … based on the generated workflow; train a …model… by using the retrieved second information to analyze trading and transactional patterns, wherein the training of the … model includes : storing the modified …, the first information, and the generated workflow …, and leveraging, …, the modified … to generate a positive feedback loop for enabling future trading behavior prediction; and forecast… at least one proposed future transaction to be executed with respect to the at least one financial instrument that relates to the first entity, wherein the forecasting comprises: forecasting a thematic concept with respect to a set of financial instruments based on outputted results… using the trained … model to analyze trading and transactional patters associated with the first knowledge graph. These limitations, as drafted, is a process that, under its broadest reasonable interpretation, but for the language of “using the at least one processor,” covers an abstract idea but for the recitation of generic computer components. That is, other than reciting “the at least one processor,” nothing in the claim elements preclude the steps from being interpreted as an abstract idea. For example, with the exception of the “the at least one processor” language, the claim steps in the context of the claim encompass an abstract idea directed to a ”Mental Process” and “Certain Methods of Organizing Human Activity.”
Dependent claims 4-6, 13-15 further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration.
Dependent claims 3, 7-9, 12, 16-18, 21, will be evaluated under Step 2A, Prong 2 below.
Step 2A, Prong 2: Independent claims 1, 10, 19, do not integrate the judicial exception into a practical application. Claim 1 is “method being implemented by at least one processor…retrieving, by the at least one processor from an internet website…; … wherein the first information includes all derivatives in an electronic data gather, analysis, and retrieval (EDGAR) database over a predetermined period of time; generating, by the at least one processor based on the first information, …; generating, by the at least one processor, at least one application programming interface (API) … the first information and the first knowledge graph; … multiple APIs…, generating, by the at least one processor via the at least one API…; retrieving, by the at least one processor…; analyzing, by the at least one processor…; modifying in real-time, by at least one processor, the at least one API; training, by the at least one processor, an artificial intelligence model that is associated with a large language model (LLM)… such that the LLM is fine-tuned so as to fully ingest structure outputs associated with the government filing, storing the modified at least one API, …, and the generated workflow in the LLM, and leveraging, via the LLM, the modified at least one API to generate a positive feedback loop for enabling future trading behavior prediction; and forecasting, by the at least one processor via the Al model, … wherein the forecasting comprises: forecasting… of the least one API… and using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. Claim 10 is a “computing apparatus for forecasting market activity, the computing apparatus comprising: a processor; a memory; and a communication interface coupled to each of the processor and the memory, wherein the processor is configured to: retrieve, from an internet website via the communication interface … wherein the first information includes all derivatives in an electronic data gathering, analysis, and retrieval (EDGAR) database over a predetermined period of time; generate at least one application programming interface (API) …; … multiple APIs…, generate, via the at least one API…, modify an API, in real-time…; train an artificial intelligence model, a large language model (LLM).. such that the LLM is fine-tuned… leveraging, via the LLM, the modified at least one API …and forecast, via the AI model,…, wherein the forecasting comprises … at least one API … using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. Claim 19 is “A non-transitory computer readable storage medium storing instructions for forecasting market activity, the storage medium comprising a second set of executable code which, when executed by a processor, causes the processor to: retrieve, from an internet website, wherein the first information includes all derivatives in an electronic data gathering, analysis, and retrieval (EDGAR) database over a predetermined period of time; … generate at least one application programming interface (API)… multiple APIs…, generate, via the at least one API,… modify in real time the at least one API; train an artificial intelligence model, a large language model (LLM) … such that the LLM is fine-tuned…, leveraging, via the LLM, the modified at least one API …and forecast, via the AI model, …, wherein the forecasting comprises… at least one API … using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). The claim employs generic computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment. This type of generally linking is not sufficient to prove integration into a practical application. See MPEP 2106.05(h).
Therefore, the additional elements of the independent claims, when considered both individually and in combination, are not sufficient to prove integration into a practical application.
Dependent claims 4-6, 13-15, further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which does not integrate the judicial exception into a practical application.
Dependent claims 3, 12, introduces the additional element of “wherein the generating of the first knowledge graph comprises using a Natural Language Processing (NLP) technique with respect to the at least one form.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claims 7, 16, introduces the additional element of “a fifth API...” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claims 8, 17, introduces the additional element of “a sixth API… a seventh API… an eighth API...” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claim 9, 18, introduces the additional element of “wherein the forecasting comprises using a result of at least one from among the sixth API, the seventh API, and the eighth API to forecast at least one from among a theme and a future exposure with respect to the single basket.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f). This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claim 21, introduces the additional element of “wherein the generating of the at least one API further includes automatically constructing additional APIs based on user behavior over time.” This limitation does not integrate the judicial exception into a practical application because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Therefore, the additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not sufficient to prove integration into a practical application.
Step 2B: Independent claims 1, 10, 19, do not comprise anything significantly more than the judicial exception. As can be seen above with respect to Step 2A, Prong 2, Claim 1 is “method being implemented by at least one processor…retrieving, by the at least one processor from an internet website…; … wherein the first information includes all derivatives in an electronic data gather, analysis, and retrieval (EDGAR) database over a predetermined period of time; generating, by the at least one processor based on the first information, …; generating, by the at least one processor, at least one application programming interface (API) … the first information and the first knowledge graph; … multiple APIs…, generating, by the at least one processor via the at least one API…; retrieving, by the at least one processor…; analyzing, by the at least one processor…; modifying in real-time, by at least one processor, the at least one API; training, by the at least one processor, an artificial intelligence model that is associated with a large language model (LLM)… such that the LLM is fine-tuned so as to fully ingest structure outputs associated with the government filing, storing the modified at least one API, …, and the generated workflow in the LLM, and leveraging, via the LLM, the modified at least one API to generate a positive feedback loop for enabling future trading behavior prediction; and forecasting, by the at least one processor via the Al model, … wherein the forecasting comprises: forecasting… of the least one API… and using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. Claim 10 is a “computing apparatus for forecasting market activity, the computing apparatus comprising: a processor; a memory; and a communication interface coupled to each of the processor and the memory, wherein the processor is configured to: retrieve, from an internet website via the communication interface … wherein the first information includes all derivatives in an electronic data gathering, analysis, and retrieval (EDGAR) database over a predetermined period of time; generate at least one application programming interface (API) …; … multiple APIs…, generate, via the at least one API…, modify an API, in real-time…; train an artificial intelligence model, a large language model (LLM).. such that the LLM is fine-tuned… leveraging, via the LLM, the modified at least one API …and forecast, via the AI model,…, wherein the forecasting comprises … at least one API … using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. Claim 19 is “A non-transitory computer readable storage medium storing instructions for forecasting market activity, the storage medium comprising a second set of executable code which, when executed by a processor, causes the processor to: retrieve, from an internet website, wherein the first information includes all derivatives in an electronic data gathering, analysis, and retrieval (EDGAR) database over a predetermined period of time; … generate at least one application programming interface (API)… multiple APIs…, generate, via the at least one API,… modify in real time the at least one API; train an artificial intelligence model, a large language model (LLM) … such that the LLM is fine-tuned…, leveraging, via the LLM, the modified at least one API …and forecast, via the AI model, …, wherein the forecasting comprises… at least one API … using the trained model to analyze trading and transactional patterns associated with the first knowledge graph. These additional elements are mere instructions to implement an abstract idea using a computer in its ordinary capacity, or merely uses the computer as a tool to perform the identified abstract idea. Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f). The claim employs generic computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment. This type of generally linking is not anything significantly more than the judicial exception. See MPEP 2106.05(h).
The additional elements of the independent claims, when considered both individually and in combination, do not comprise anything significantly more than the judicial exception.
Dependent claims 4-6, 13-15, further narrow the abstract idea identified in the independent claims and do not introduce further additional elements for consideration, which is not anything significantly more than the judicial exception.
Dependent claims 3, 12, introduces the additional element of “wherein the generating of the first knowledge graph comprises using a Natural Language Processing (NLP) technique with respect to the at least one form.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f). This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claims 7, 16, introduces the additional element of “a fifth API.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f). This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claims 8, 17, introduces the additional element of “a sixth API… a seventh API… an eighth API...” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f). This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claim 9, 18, introduces the additional element of “wherein the forecasting comprises using a result of at least one from among the sixth API, the seventh API, and the eighth API to forecast at least one from among a theme and a future exposure with respect to the single basket.” Use of a computer or other machinery in its ordinary capacity for performing the steps of the abstract idea or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., certain methods of organizing human activity) is not anything significantly more than the judicial exception. See MPEP 2106.05(f). This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
Dependent claim 21, introduces the additional element of “wherein the generating of the at least one API further includes automatically constructing additional APIs based on user behavior over time.” This limitation is not anything significantly more than the judicial exception because it is nothing more than generally linking the use of the judicial exception to a particular technological environment. See MPEP 2106.05(h).
The additional elements of the dependent claims, when considered both individually and in the context of the independent claims, are not anything significantly more than the judicial exception.
Accordingly, claims 1, 3-10, 12-19, 21, are rejected under 35 USC 101.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3-10, 12-19, 21, are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 1 recites “a first API that identifies a market identifier associated with the first entity.” The originally filed specification discloses only “a first API that is designed to identify a stock ticker” see ¶ 72. “Market identifier” does not appear in the original disclosure as filed, and it is unclear whether it is intended as a broader genus encompassing more than a stock ticker. If so the specification does not appear to reasonably convey possession of that broader concept. The applicant is required either to amend the claim to recite “stock ticker” consistent with the disclosure, or identify where the broader term “market identifier” has support. Claim 1 also includes the language of “a fourth API that determines a future behavior of the second entity in relation the market identifier.” The applicant has support in the originally filed disclosure for an API as “a fourth API that is designed to determine
a future buying behavior of the first institution with respect to a stock associated with the first entity.” The claimed “future behavior” as opposed to the previously claimed “future buying behavior” as well as the language of “the market identifier” as opposed to “a stock” broaden the claim beyond what is disclosed in the originally filed disclosure. The applicant is required either to amend the claim to recite “future buying behavior” and/or “stock ticker” consistent with the disclosure, or identify where the broader term “future behavior” and/or “market identifier” has support. A description of a specific species does not by itself provide adequate written description support for a broader claimed genus encompassing the species. To satisfy the written description requirement, an applicant must convey with reasonable clarity to those skilled in the art that, as of the filing date sought, the inventor was in possession of the invention, and that the invention, in that context, is whatever is now claimed. The test for sufficiency of support in a parent application is whether the disclosure of the application relied upon “reasonably conveys to the artisan that the inventor had possession at that time of the later claimed subject matter.” The possession of the species does not convey possession of the full scope of a later claimed genus. Appropriate action is required.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 3-10, 12-19, 21, are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 10, 19, recite the limitation "the entity" in the second generat[ing] step. There is insufficient antecedent basis for this limitation in the claim.
Regarding claims 1, 10, 19, the phrase "a fourth API that determines a future behavior of the second entity in relation the market identifier" renders the claim indefinite because the limitation appears to be missing the word “to”, and as written it is unclear what relationship is being claimed between the future behavior and the market identifier.
The claims that dependent from a previously rejected claim inherit the rejection of the claim from which they depend.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMIE H AUSTIN whose telephone number is (571)272-7363. The examiner can normally be reached Monday, Tuesday, Thursday, Friday 7am-2pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian Epstein can be reached at (571) 270 5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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JAMIE H. AUSTIN
Examiner
Art Unit 3625
/JAMIE H AUSTIN/Primary Examiner, Art Unit 3625
